The Experts below are selected from a list of 4747401 Experts worldwide ranked by ideXlab platform
Osamu Ochiai - One of the best experts on this subject based on the ideXlab platform.
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big data challenges in building the global earth observation System of Systems
Environmental Modelling and Software, 2015Co-Authors: Stefano Nativi, Paolo Mazzetti, Mattia Santoro, Fabrizio Papeschi, Max Craglia, Osamu OchiaiAbstract:There are many expectations and concerns about Big Data in the sector of Earth Observation. It is necessary to understand whether Big Data is a radical shift or an incremental change for the existing digital infrastructures. This manuscript explores the impact of Big Data dimensionalities (commonly known as 'V' axes: volume, variety, velocity, veracity, visualization) on the Global Earth Observation System of Systems (GEOSS) and particularly its common digital infrastructure (i.e. the GEOSS Common Infrastructure). GEOSS is a global and flexible network of content providers allowing decision makers to access an extraordinary range of data and information. GEOSS is a pioneering framework for global and multidisciplinary data sharing in the EO realm. The manuscript introduces and discusses the general GEOSS strategies to address Big Data challenges, focusing on the cloud-based discovery and access solutions. A final section reports the results of the scalability and flexibility performance tests. Display Omitted Big Data challenges for the Global Earth Observation System of Systems (GEOSS).GEOSS Common Infrastructure (GCI) solutions to address Big Data challenges.The role played by the GEO Brokering framework (GEO DAB).GEO DAB cloud configuration.Performance Tests.
Keith W Hipel - One of the best experts on this subject based on the ideXlab platform.
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a data centric capability focused approach for System of Systems architecture modeling and analysis
Systems Engineering, 2013Co-Authors: Keith W Hipel, Kewei Yang, Yingwu ChenAbstract:A data-centric, capability-focused approach is proposed to facilitate the architecture modeling and analysis of challenging System-of-Systems (SoS). This approach abstracts essential information from the underlying complexity with the architecture modeling in a data-centric and semantically consistent fashion, and allows early understanding and exploration of the logical, behavioral, and performance characteristics to achieve the desired capabilities. More specifically, a high-level data meta-model, depicting the semantic relationships of constituent architectural data elements, is first presented to guide the architectural data modeling, which is aligned well with the US Department of Defense Architecture Framework (DoDAF) Meta-model (DM2). Then, the development of architectural descriptions and the construction of executable models are studied based on the core architectural data elements. Additionally, architecture analysis using static and executable models are discussed, including static analysis, dynamic analysis, and experimental analysis. The feasibility of the foregoing approach is demonstrated with an illustrative example. ©2013 Wiley Periodicals, Inc. Syst Eng 16:
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System of Systems engineering and risk management of extreme events concepts and case study
Risk Analysis, 2012Co-Authors: Michele Bristow, Liping Fang, Keith W HipelAbstract:The domain of risk analysis is expanded to consider strategic interactions among multiple participants in the management of extreme risk in a System of Systems. These risks are fraught with complexity, ambiguity, and uncertainty, which pose challenges in how participants perceive, understand, and manage risk of extreme events. In the case of extreme events affecting a System of Systems, cause-and-effect relationships among initiating events and losses may be difficult to ascertain due to interactions of multiple Systems and participants (complexity). Moreover, selection of threats, hazards, and consequences on which to focus may be unclear or contentious to participants within multiple interacting Systems (ambiguity). Finally, all types of risk, by definition, involve potential losses due to uncertain events (uncertainty). Therefore, risk analysis of extreme events affecting a System of Systems should address complex, ambiguous, and uncertain aspects of extreme risk. To accomplish this, a System of Systems engineering methodology for risk analysis is proposed as a general approach to address extreme risk in a System of Systems. Our contribution is an integrative and adaptive Systems methodology to analyze risk such that strategic interactions among multiple participants are considered. A practical application of the System of Systems engineering methodology is demonstrated in part by a case study of a maritime infrastructure System of Systems interface, namely, the Straits of Malacca and Singapore.
Stefano Nativi - One of the best experts on this subject based on the ideXlab platform.
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big data challenges in building the global earth observation System of Systems
Environmental Modelling and Software, 2015Co-Authors: Stefano Nativi, Paolo Mazzetti, Mattia Santoro, Fabrizio Papeschi, Max Craglia, Osamu OchiaiAbstract:There are many expectations and concerns about Big Data in the sector of Earth Observation. It is necessary to understand whether Big Data is a radical shift or an incremental change for the existing digital infrastructures. This manuscript explores the impact of Big Data dimensionalities (commonly known as 'V' axes: volume, variety, velocity, veracity, visualization) on the Global Earth Observation System of Systems (GEOSS) and particularly its common digital infrastructure (i.e. the GEOSS Common Infrastructure). GEOSS is a global and flexible network of content providers allowing decision makers to access an extraordinary range of data and information. GEOSS is a pioneering framework for global and multidisciplinary data sharing in the EO realm. The manuscript introduces and discusses the general GEOSS strategies to address Big Data challenges, focusing on the cloud-based discovery and access solutions. A final section reports the results of the scalability and flexibility performance tests. Display Omitted Big Data challenges for the Global Earth Observation System of Systems (GEOSS).GEOSS Common Infrastructure (GCI) solutions to address Big Data challenges.The role played by the GEO Brokering framework (GEO DAB).GEO DAB cloud configuration.Performance Tests.
Li-chen Zhang - One of the best experts on this subject based on the ideXlab platform.
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applying System of Systems engineering approach to build complex cyber physical Systems
International Conference on Systems Engineering, 2015Co-Authors: Li-chen ZhangAbstract:Cyber physical Systems are growing in scale and complexity. The cyber physical Systems such as transportation Systems and aerospace Systems are Systems of Systems that are large scale concurrent and distributed Systems and comprised of complex Systems. In order to specify and model such kind of Systems, we need develop specification and modeling methods which would be capable to encompass the Systems of Systems (SoS) specific properties of cyber physical Systems. In this paper, we propose a new paradigm for specifying and modeling cyber physical Systems based on System-of-Systems approach. In this paper, we extend AADL in modeling dynamic continuous aspect and spatial aspect, and integrate AADL with Modelica, and formal methods to specify and model cyber physical Systems based on System-of-Systems approach. We specify cyber part of cyber physical Systems with, and model physical part of cyber physical Systems with Modelica. We apply formal specification method in requirement analysis process in order to ensure that the software requirements model satisfies required System function and performance goals and constraints, including safety. The effectiveness of the approach is demonstrated with a case study of Vehicular Ad-hoc NETwork.
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Modeling large scale complex cyber physical control Systems based on System of Systems engineering approach
Automation and Computing (ICAC), 2014 20th International Conference on, 2014Co-Authors: Li-chen ZhangAbstract:Most cyber physical Systems are composed of subSystems. The subSystems themselves may have smaller sub-Systems. Complex cyber physical Systems rely heavily on the interplay of dozens of individual sub-Systems. Thus, cyber physical Systems are typical System of Systems (SoS). In order to specify and model such kind of Systems, we need develop specification and modeling methods which would be capable to encompass the Systems of Systems (SoS) specific properties of cyber physical Systems. In this paper, we propose a new paradigm for specifying and modeling automotive cyber physical Systems based on System-of-Systems approach. In this paper, we propose an approach to support specification and modeling automotive cyber physical Systems based on Systems of Systems engineering in the well established modeling language Modelicaml. The main aim of ModelicaML is to enable an efficient and effective way to use Modelica, UML and SysML models reusing notations that are also used for software modeling. We apply formal specification method in requirement analysis process in order to ensure that the software requirements model satisfies required System function and performance goals and constraints, including safety. The effectiveness of the approach is demonstrated with a case study of Vehicular Ad-hoc NETwork.
Jiang Zhiping - One of the best experts on this subject based on the ideXlab platform.
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simulation validation method for capability requirement of weapon System of Systems based on petri net
Computer Simulation, 2009Co-Authors: Jiang ZhipingAbstract:To validate whether the combat capabilities that weapon System of Systems provide satisfy the capabilities that combat tasks need,the simulation validation method for the System of Systems capability requirement based on the Petri net was provided. Firstly,the formal description method for the combat task and its combat capability requirement was researched. Secondly,the formal description method for the combat capability of the System of Systems was researched. Thirdly,it was researched that how to create the simulation model based on the Petri constraint by probability and resource. Lastly,the case that proved the method's availability was analyzed.
